detect.py 文件源码

def find_biggest_contour(image):
    # Copy
    image = image.copy()
    #input, gives all the contours, contour approximation compresses horizontal,
    #vertical, and diagonal segments and leaves only their end points. For example,
    #an up-right rectangular contour is encoded with 4 points.
    #Optional output vector, containing information about the image topology.
    #It has as many elements as the number of contours.
    #we dont need it
    _, contours, hierarchy = cv2.findContours(image, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)

    # Isolate largest contour
    contour_sizes = [(cv2.contourArea(contour), contour) for contour in contours]
    biggest_contour = max(contour_sizes, key=lambda x: x[0])[1]

    mask = np.zeros(image.shape, np.uint8)
    cv2.drawContours(mask, [biggest_contour], -1, 255, -1)
    return biggest_contour, mask